Build Your Own AI Project Worksheet

AI for students lesson 23: Design a tiny AI project · Set 381 · 40 questions

AI tip (Accuracy = correct ÷ total × 100): Steps: 1 choose a problem → 2 collect examples → 3 label them → 4 check and correct bad labels (clean the data) → 5 split into training and test sets → 6 train → 7 test with new examples → 8 measure accuracy → 9 improve the data and retest. Accuracy = correct ÷ total × 100. Wrong = total − correct. Expected right = accuracy ÷ 100 × total. Keep some examples apart for testing (for example one fifth); the rest are for training.

1. 1.❌ Kabir’s spam spotter was tested on 43 new messages and got 35 right. How many did it get wrong?
2. 2.📋 Planning an AI project: which comes first — fix it and test again or train the model? (a) fix it and test again (b) train the model
3. 3.🧪 Your fruit sorter mixes up oranges and lemons. What helps most? (a) a new colour screen (b) more labelled examples (c) fewer examples (d) a louder speaker
4. 4.⚖️ Two fruit sorter models were tested on the same 10 fruit photos. Model A got 10 right and Model B got 7 right. How many percentage points more accurate is Model A?
5. 5.📋 Planning an AI project: which comes first — fix it and test again or correct bad labels? (a) fix it and test again (b) correct bad labels
6. 6.🎯 Aarav’s handwriting reader was tested on 25 new handwritten letters and got 22 right. What is its accuracy in percent?
7. 7.🧪 What is accuracy? (a) total × 2 (b) correct + total (c) correct ÷ total × 100 (d) total − correct
8. 8.📋 Planning an AI project: which comes first — fix it and test again or try unseen examples? (a) fix it and test again (b) try unseen examples
9. 9.⚖️ Two handwriting reader models were tested on the same 10 handwritten letters. Model A got 10 right and Model B got 8 right. How many percentage points more accurate is Model A?
10. 10.📦 Ananya collected 120 labelled leaf photos for a leaf identifier and keeps one fifth of them for testing. How many are left for training?
11. 11.📦 Arjun collected 50 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
12. 12.📋 Planning an AI project: which comes first — correct bad labels or work out the accuracy? (a) correct bad labels (b) work out the accuracy
13. 13.🎯 Diya’s handwriting reader was tested on 25 new handwritten letters and got 21 right. What is its accuracy in percent?
14. 14.📋 Planning an AI project: which comes first — test on new photos or calculate percent right? (a) test on new photos (b) calculate percent right
15. 15.⚖️ Two recycling sorter models were tested on the same 50 waste photos. Model A got 50 right and Model B got 48 right. How many percentage points more accurate is Model A?
16. 16.📋 Planning an AI project: which comes first — work out the accuracy or test on new photos? (a) work out the accuracy (b) test on new photos
17. 17.📦 Aarav collected 120 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
18. 18.🧪 Why must you test a model on examples it has NOT seen? (a) to see if it learned (b) to make it faster (c) to save paper (d) to make it bigger
19. 19.📦 Meera collected 180 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
20. 20.📋 Planning an AI project: which comes first — pick a question to solve or collect fruit photos? (a) pick a question to solve (b) collect fruit photos
21. 21.🎯 Vihaan’s spam spotter is 80% accurate. If it is tested on 20 new messages, how many should it get right?
22. 22.🧪 You can plan a simple AI project with… (a) paper and examples (b) only a big robot (c) nothing at all (d) a secret password
23. 23.🎯 Ishaan’s bird-song app was tested on 10 new bird songs and got 5 right. What is its accuracy in percent?
24. 24.❌ Vihaan’s handwriting reader was tested on 16 new handwritten letters and got 14 right. How many did it get wrong?
25. 25.🎯 Diya’s fruit sorter is 90% accurate. If it is tested on 30 new fruit photos, how many should it get right?
26. 26.📋 Planning an AI project: which comes first — work out the accuracy or try unseen examples? (a) work out the accuracy (b) try unseen examples
27. 27.📦 Rohan collected 80 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
28. 28.⚖️ Two recycling sorter models were tested on the same 10 waste photos. Model A got 10 right and Model B got 9 right. How many percentage points more accurate is Model A?
29. 29.📋 Planning an AI project: which comes first — split train and test or tag each photo by type? (a) split train and test (b) tag each photo by type
30. 30.⚖️ Two recycling sorter models were tested on the same 20 waste photos. Model A got 17 right and Model B got 16 right. How many percentage points more accurate is Model A?
31. 31.📦 Kabir collected 50 labelled handwritten letters for a handwriting reader and keeps one fifth of them for testing. How many are left for training?
32. 32.📦 Diya collected 50 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
33. 33.📦 Kabir collected 190 labelled messages for a spam spotter and keeps one fifth of them for testing. How many are left for training?
34. 34.📋 Planning an AI project: which comes first — collect fruit photos or calculate percent right? (a) collect fruit photos (b) calculate percent right
35. 35.🎯 Saanvi’s spam spotter was tested on 4 new messages and got 3 right. What is its accuracy in percent?
36. 36.📦 Diya collected 110 labelled fruit photos for a fruit sorter and keeps one fifth of them for testing. How many are left for training?
37. 37.❌ Vihaan’s spam spotter was tested on 45 new messages and got 43 right. How many did it get wrong?
38. 38.🎯 Rohan’s fruit sorter was tested on 20 new fruit photos and got 14 right. What is its accuracy in percent?
39. 39.❌ Kabir’s spam spotter was tested on 19 new messages and got 16 right. How many did it get wrong?
40. 40.📋 Planning an AI project: which comes first — correct bad labels or train the model? (a) correct bad labels (b) train the model

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